Published Paper Details:

As we all know big data is used anywhere and everywhere, a big data is a large diverse set of structured, semi-structured and unstructured data. Here we are discussing about use of big data in bioinformatics. A project of bioinformatics to identifying protein disulfide bonds. Disulfide bonds (SS) are post-translational modifications important for the proper folding and stabilization of any cellular proteins with the rapeuticuses, including antibodies and other biologics. With budding advances of biologics and biosimilar, there is a mounting need for a robust method for accurate identification of SS. Even though several mass spectrometry methods have emerged for this task, their practical use rests on the broad effectiveness of both sample preparation methods and bioinformatics tools. Here we present a new protocol tailored toward mapping SS; it uses readily available reagents, instruments, and software. For sample preparation, a 4-h pepsin digestion at pH1.3 followed by an overnight trypsin digestion at pH6.5 can maximize the release of SS-containing peptides from non-reduced proteins, while minimizing SS scrambling. For LC/MS/MS analysis, SS-containing peptides can be efficiently fragmented with HCD in a Q Enactive Orbitrap mass spectrometer, preserving SS for subsequent identification. Our bioinformatics protocol describes how we tailored our freely downloadable and easy-to-use software, Spectrum Identification Machine for Cross-Linked Peptides (SIMXL), to minimize false identification and facilitate manual validation of SS-peptide mass spectra. To substantiate this optimized method, we've comprehensively identified 14 out of 17 known SS in BSA.